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The Un-Notebook Notebook: Scientific Analysis Environment

Project description

The un-notebook notebook: an interactive scientific analysis environment.

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About Cauldron

Cauldron combines the crucial workflow of notebook-style editing:

  • Data Persistence: Shared variables are stored in memory between executions to avoid having to run every step from the beginning each time.

  • Accessible HTML Output: Output is written to notebook-style formatted HTML for efficient display, consumption and sharing.

  • Segmented Code Execution: Code is run in distinct steps (just like notebook cells), and you control when and which steps are run.

with the best elements of traditional software development workflow:

  • Your Choice of IDE: Modern modern IDEs have excellent productivity features like extensive customization, real-time error checking, intelligent code completion and efficient project navigation. Use whichever one works best for you.

  • Straight to Production: Cauldron projects can be run in non-interactive mode as well as run from inside other python applications, which makes it easy to productionize and deploy an analysis when it’s ready.

  • Clean Version Control: Common version control actions like diff-ing and merging are obstructed when the code is embedded in notebook files. In Cauldron, where code is stored in independent code files, you can take full advantage of version control functionality.

  • Code Review Friendly: Embedded notebook code also makes reviews cumbersome to say the least. Cauldron’s independent code files provide all of the flexibility available to traditional code review.

With Cauldron you write code in your choice of interactive development environment (IDE) or text editor, and run it using the Cauldron shell like a notebook. The result is a notebook-style HTML output page, without the traditional drawbacks of notebooks.

Installation

The latest release of Cauldron is available from both PyPi:

$ pip install cauldron-notebook

and Anaconda:

$ conda install -c sernst cauldron

Because Cauldron is still in the early stages of development and rapidly evolving, the latest releases can lag behind the development version. If you want keep up with the latest developments, install directly from the Github page instead of from PyPi:

$ pip install git+https://github.com/sernst/cauldron.git

Or you can install in development mode if you want to manage updates using git instead of pip. To install in that way, clone a local copy of this repository to your local machine and, inside a terminal, cd into your local copy directory and run the command:

$ python3 setup.py develop

Getting Started

Once the installation is complete, you’ll have access to the Cauldron shell from a terminal. Cauldron is a shell-based program you start from a terminal with the cauldron command:

$ cauldron

Once started, the Cauldron shell provides all of the functionality you need to manage your analysis projects through a collection of commands. To see a list of available commands and their basic descriptions use the ? or help command on the Cauldron prompt:

<>: ?

or:

<>: help

For more detailed information on a specific command use the help command along with the name of the command you wish to learn more about. For example, to get help on the open command, you would enter:

<>: help open

on the Cauldron prompt.

Example Projects

Cauldron comes bundled with a few example projects for demonstration purposes. To open one of these projects, use the command:

<>: open @examples:[EXAMPLE_PROJECT_NAME]

where [EXAMPLE_PROJECT_NAME] is the name of an existing example project. The @examples: prefix is an alias in Cauldron that resolves to the path where the example files are stored. You can also create your own aliases, which will be explained in detail later.

Like all commands in Cauldron, the open command supports tab auto-completion. If you enter the beginning of the command above:

<>: open @examples:

and hit the tab key with the cursor at the end of the line, Cauldron will give you a list of the example project subdirectories.

A good example to start would be Cauldron’s hello_cauldron:

<>: open @examples:hello_cauldron/

Once this command is run, the hello_cauldron project will be opened and readied for you to run. The Cauldron shell prompt updates to reflect the open project. Instead of <>:, which signifies no open project, the prompt should now be <hello_cauldron>:.

If you now enter the run command without any arguments, all steps (cells) in the project will run:

<hello_cauldron>: run

Once complete, you can view the current state of the notebook display with the show command:

<hello_cauldron>: show

which opens the current project display file in your default browser. When you are finished working on a project, you use the close to command:

<hello_cauldron>: close

This empties all of the information Cauldron has been storing for your project in memory, and takes you back to the initial command prompt where you started:

<>:

Tutorial: First Project

This tutorial walks through creating your first project. It mirrors the @example:hello_cauldron project that comes installed with Cauldron.

Create New Project

To create your first project run the Cauldron shell command:

<>: create hello_cauldron @home:

For more details about the create command, use the Cauldron shell command:

<>: help create

The create command takes two arguments:

  1. The name of your new project (hello_cauldron in the example above)

  2. The absolute path to the directory where the project will be saved. In the example above, the @home: argument is a shortcut to Cauldron’s default home directory, which is ~/cauldron/.

When the example create command above is executed, a hello_cauldron project will be created in the directory ~/cauldron/hello_cauldron/, with the scaffolding for the project already written. The create command also immediately opens the new project in the shell.

Add First Code Step

Now that the project has been created, you need to add some code to it. To do that, use the steps add command:

<hello_cauldron>: steps add create_data.py

This will create a new step called S01-create_data.py in your project directory and add it to the Cauldron project. Notice that the name you gave the step and the one actual step name are different. There’s an S01- prefix added to the file. This prefix is added automatically by Cauldron to help you organize your files. You can disable this feature when you create a project if you really want to manage the names all yourself, but we’ll get into that in an advanced tutorial.

The step file you created is ready to be modified. Open the S01-create_data.py step file in your choice of Python code editor. You’ll find the file in the project directory, which is ~/cauldron/hello_cauldron/. Add the following code to the S01-create_data.py file:

import numpy as np
import pandas as pd
import cauldron as cd

df = pd.DataFrame(
    np.random.randn(10, 5),
    columns=['a', 'b', 'c', 'd', 'e']
)

cd.display.header('Random Data Frame:')
cd.display.table(df)

cd.shared.df = df

Once you’ve saved that code to the S01-create_data.py file, you can run your project using the run command:

<hello_cauldron>: run

Then use the show command to see the results:

<hello_cauldron>: show

The project display file will open in your default browser.

Add Another Step

Now we’ll add another code step to plot each column in our DataFrame. Once again use the steps command:

<hello_cauldron>: steps add plot_data.py

Open the S02-plot_data.py step file and add the following code:

import matplotlib.pyplot as plt
import cauldron as cd

df = cd.shared.df

for column_name in df.columns:
    plt.plot(df[column_name])

plt.title('Random Plot')
plt.xlabel('Indexes')
plt.ylabel('Values')

cd.display.pyplot()

We used matplotlib for this tutorial, but Cauldron also supports Seaborn, Bokeh, Plotly or any other Python plotting library that can produce an HTML output. There are Cauldron example projects showing how to plot using each of these libraries.

Now run the project again:

<hello_cauldron>: run

You’ll notice that the shell output looks like:

=== RUNNING ===
[S01-create_data.py]: Nothing to update
[S02-plot_data.py]: Updated

The S01-create_data.py step was not run because it hasn’t been modified since the last time you executed the run command. Just like other notebooks, the results of running a step (cell) persist until you close the project and do not need to be updated each time. Cauldron watches for changes to your files and only updates steps if the files have been modified, or an early step was modified that may affect their output.

Now you can view the updated project display simply by refreshing your browser. However, if you already closed the project display browser window, you can show it again at any time with the show command.

And that’s that. You’ve successfully created your first Cauldron project. You can close your project with the close command:

<hello_cauldron>: close

Or, if you want to exit the Cauldron shell at any time, use the exit command:

<>: exit

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